What Can the Price Gap Between Branded and Generic Tell Us About Markups?
Robert Barsky, University of Michigan and NBER
Mark Bergen, University of Minnesota
Shantanu Dutta, University of Southern California
Daniel Levy, Emory University
Very Preliminary Draft
For Presentation at the Conference on Income and Wealth,
Scanner Data and Price Indexes.
September 15-16, 2000
The authors would like to thank Ning Liu for her outstanding research assistance, Susanto
Basu, Kai-Uwe Kuhn, Jim Levinsohn, Steve Salant, Mathew Shapiro for many helpful
discussions, and Steve Hoch for access to his survey on national brand/private label quality
differences, and both the University of Chicago for access to the data.
Abstract
In this paper we investigate the size of markups for nationally branded products sold in the
U.S. retail grocery industry. Our approach to estimating these markups is to treat the price
of the comparable private label product as an upper bound for the marginal costs faced by
the branded manufacturer. Using scanner data from a large Midwestern grocery chain we
estimate the markup ratios for over 200 products in 19 categories. This data includes not
only the prices and quantities sold by UPC, but also the retailers’margins on each
product, which allows us to measure the markup ratios for national brands based on
wholesale rather than retail prices. We find that markup ratios measured this way range
from 2.5 for crackers and 2.3 in the analgesics category to 1.2 in canned tuna, with the
majority of categories in the range 1.4 to 1.7. These data also allow us to measure
retailer’s markups over wholesale costs. We find that retailer’s markups are generally
lower for nationally branded products than for private labels. The net effect of this is that
markup ratios measured using only retail price data will understate the markups for
nationally branded products.
I. Introduction
The magnitude of marginal costs and markups over marginal cost are empirical
questions of considerable general interest in economics. Microeconomists are interested in
markups because they bear on such questions as the relevance of alternative models of
imperfect competition, the welfare consequences of market power, and the benefits of new
product introduction. In recent macroeconomic research as well, markups play a central
role. Although macroeconomic discourse most often focuses on the cyclicality rather than
the level of markups, the degree of cyclicality is often limited by the absolute size of the
markup (Rotemberg and Saloner 1986).
The estimation of markups is difficult because of the unobservability of marginal cost.
There are essentially two ways in which inference about markups and marginal cost is
approached in the econometric literature. One approach is via the cost function, which is
either inferred directly from engineering data or estimated from cross-sectional or time
series market data. The other is to estimate consumer demand functions, and compute the
markup based on estimated demand elasticities.
This paper takes a quite different approach to the estimation of marginal costs and
markups. We take the price of a “private label” equivalent or near-equivalent product as a
proxy for marginal cost. Since the private label product would not be sold at less than its
marginal cost, and if the two products are produced under sufficiently similar conditions,
then the ratio of the price of the branded product to that of the private label would serve
as a lower bound for the markup ratio for the branded product1.
Roughly speaking, the story we tell is the following. Private label products are
physically identical to nationally branded products, but because “brands” appears in the
utility function, the branded product commands a higher market price. At the same time,
however, many of the promotional expenses which vertically differentiate the branded
product from its private label counterpart appear largely as sunk or at least fixed costs,
marginal production costs of private label products are therefore not systematically lower
1
This appraoch has been used informally in the past. The text by Carlton and Perlof (1994) and a recent
paper by Nevo (1997) applies this method in passing for breakfast cereals, although its principal content
lies elsewhere.
than marginal costs for branded products. The high ratio of branded price to private label
price is thus indicative of substantial markups. On average, markups estimated in this
manner are on the high side of, though consistent with, those found in previous studies.
For the national brands with the highest visibility or brand capital, markups are particularly
large, on the order of 100%.
We apply this approach to products in the grocery industry. This is an appropriate
place to apply this measure because there are many “private label” products in a wide
variety of categories. Perhaps it is best to begin with a brief historical account of private
labels in this industry. Fitzell (1998), in his book on private labels, recounts that "private
labels in the grocery segment evolved out of bulk commodity staples, first into packaged
teas, sugar, flour, spices, etc. Early in this century, private label development was
expanded further into canned vegetables and fruits, frozen foods, and bakery and dairy
products. Other product categories followed: paper products, detergents, deli items, soft
drinks, health and beauty care products, general merchandise, and perishables such as
meats, poultry and produce … With few exceptions, the packaged goods product mix has
been the central focus of private label business in the retail store … The parameters for
private label have been extended virtually into every product category found in retail
outlets. Private label has tapped into untouchable product categories of the recent past:
cosmetics, baby food, natural health products, gourmet delicacies, etc." It is important to
note that the products sold under the private label of Dominick’s finer foods are not
generics, and are in fact labeled in a way which provides some, but not all, of the functions
of branding. The particular version of branding that Dominick’s offers substantially
reduces uncertainty about the quality of the product, in particular concerns that the store
brand may exhibit physical inferiority.
Further, there are reasons to believe that private labels make a reasonable proxy for
the marginal costs of nationally branded products. First, we were able to access a survey
of quality assurance managers at the top 50 retail grocery chains from retailers where they
rate the quality comparability of private labels and national brands. Although this varies by
category, this survey suggests that on the whole private labels are fairly comparable. This
is consistent with the prevailing wisdom in consumer reports and other sources in the
business and trade press. Second, in discussions with private label managers it was their
belief that the production costs of nationally branded products would be the same or
higher for comparable private label products. This was due to the size and scale
advantages national brands have in terms of packaging, production and input prices. Third,
private labels have the same sources of marginal costs as national brands, and differ in
areas that are related to more fixed costs, in this industry. Specifically private labels do not
spend as significantly on R&D and advertising as national brands do. Their costs are
almost completely made up of production, packaging and distribution costs.
We compute this mark ups using scanner data.2 The grocery industry has scanner data
available to make these estimates for a wide variety of products and categories.
Additionally, the Dominick’s dataset we use in this paper has the unique feature of
incorporating retail margins as used by managers making the pricing decisions at this
chain. Thus, we are able to report markups based on the wholesale prices received by
nationally branded manufacturers as well as the markups retailers receive on both
nationally branded and private label products. This allows us to decompose the markups
that can be calculated from retail prices into the different participants in the channel of
distribution. In section V we report these markups for over 200 nationally branded
products in 19 product categories (see tables 1 - 23).
The paper is structured as follows. In the next section introduces our data and
empirical methods. We proceed to present “markup” data, at both the wholesale and retail
levels, for a wide range of products for which both national brand and private label prices
are available. We discuss the implications of these results in the conclusion.
II. Inferring Marginal Cost and Markups From Private Labels
Our method to measure markups relies on the assumption that we can use the price of
private labels to infer the marginal production cost of national brands. Since the generic
would not be sold at less than its marginal cost, the price gap can thus be seen as a lower
bound on the markup on the brand-name version. The natural question that arises is when
2
This data set has been used to study economic issues by authors including (Chevalier et. al. 2000; Muller
et. al 2000; Bergen et. al. 1998; Dutta et. al 1999).
is it okay to treat the brand and the generic as equivalent products, for the sake of
inferring marginal cost.
At a broad level, we know these are different goods by virtue of their carrying a
different brand name and that customers pay different prices for them. Thus, the principal
issues involve finding out how the branded products are different from the private labels.
To the degree that there are not substantial differences in terms of variable costs, and the
differences relate to fixed costs, we are on safe ground using our measure of markups. To
the degree that the differences are in terms of variable costs borne by branded
manufacturers, then our measure may be overestimating markups and would be less
appropriate. In this industry there are two major sources of differences that could be
variable cost in nature: 1) private label goods are inferior products produced by lower
cost methods (the “physical quality” issue) and 2) even if the private label product is
physically comparable to the nationally branded version, the expense of advertising, and
otherwise promoting the national brand must be taken account of, and these may create
additional marginal costs for national brands (the “marketing cost” objection).
In this section we present the evidence we have found which suggests that, in fact, it
is reasonable to assume that the differences between national brands and private labels are
not likely to be variable costs for many products sold in this industry. We are still in the
process of gathering additional evidence at the level of particular product categories or
national brand/private label pairs to better understand exactly where this assumption is
appropriate in this industry. Finally, we should mention that this is a conservative
assumption for many nationally branded products in this context because private label
manufacturers also have a markup that is not considered in our analysis, which will only
cause our measure to understate markups. With these caveats in mind, we now turn to
each issue in more detail.
A. The Physical Quality Issue
We began our process by going to the field and interviewing a number of industry
experts on private labels. Their sense was that for products of equal quality, the costs of
producing private labels were likely to be the same, or perhaps higher, than for national
brands. One manager put it best when he said,
"national brands should be able to physically produce at a lower cost … they are
able to negotiate lower costs on components and vertically integrate to do processes
themselves rather than having to buy at higher marginal costs." (VP private label food
broker)
Quality
This suggests that the first thing we have to find out is whether private labels in this
industry are indeed of similar quality, and if so which ones are more reasonable to use in
our study. Hoch and Banerji (1993), noting the absence of secondary data source on
private label quality comprehensive enough to cover all the SAMI product categories3,
undertook a survey of quality assurance managers at the fifty largest supermarket chains
and grocery wholesalers in the United States (according to Thomas Food Industry
Register). The companies were widely dispersed across the country. These managers
typically have graduate education in food science and have wide experience testing
numerous product categories. Hoch and Banerji contacted each of these managers by
telephone to solicit their participation, and followed up with a questionnaire. Thirty-two
people (64%) returned the survey, resulting in twenty-five usable sets of responses (50%).
The results reported are the average of these responses. For each of the original SAMI
categories the experts were asked: “How does the quality of the best private label supplier
compare to the leading national brands in the product category?”4 The respondents gave a
rating on a five point scale where using a one suggests that private labels are much worse
in quality than the national brands while using a 5 suggests that these experts think that the
private label quality is comparable to that of the national brand.
Since their primary focus lay elsewhere, Hoch and Banerji did not report the raw data
from the quality survey. However, these authors graciously supplied us with the means of
3
For example, Consumer Reports typically review consumer packaged goods less than once per issue,
therefore it does not have quality ratings of all the products that we have in the data set.
4
The experts received a one-page set of instructions explaining what we meant by each question and how
to use the scales. The question on quality measures the retailer's ability to procure high-quality private
labels. This was meant to capture "objective" quality rather than quality as perceived by customers.
their survey-based quality rating for each of the categories that we examine in the
Dominick’s data, and we report these in Exhibit 1.
Exhibit 1: Product Category Ratings by Category*
Product Category
Ratings on quality of Private Label
Analgesics
4.8
Toothbrushes
4.7
Frozen Juices
4.7
Cereals
4.7
Oatmeals
4.7
Crackers
4.6
Cheeses
4.6
Frozen Entrees
4.6
Canned Tuna
4.5
Fabric Softeners
4.5
Bottled Juices
4.5
Laundry Detergents
4.4
Snack Crackers
4.4
Cookies
4.3
Grooming Products
4.3
Dish Detergents
4.2
Toothpastes
4.2
Canned Soup
4.1
Bathroom Tissues
4.1
Soft Drinks
4.0
*We thank Steve Hoch for providing us this data.
At the same time, the survey does have some limitations. Hoch and Banerji (1993)
mention that “it is most likely that the experts were partisan to private labels” since “one
aspect of their jobs involves monitoring and improving private label quality”. In order to
check whether there was any serious bias in the ratings they received, they went through
each issue of consumer reports for the past 6 years and found evaluations of 36 of the
same product categories rated by the quality control experts. For each of these categories
the consumer report provides rank order quality information for leading national brands
and some selected private labels. They find that the ratings from the managers were highly
correlated to those in the consumer report where available. Thus the ratings seem to be a
reasonable indicator of the private label quality relative to the national brands.
Hoch and Banerji’s (1993, p. 62) own evaluation of the evidence is that “the over
riding sentiment of these experts was that quality of the best private label was quite close
to that of the national brands”. This is consistent with industry observers (e.g. Quelch
1996; Fitzell 1998) who suggest that while over the long haul private label products have
not consistently exhibited the uniformly high quality standards as national brands, in recent
years private label products have significantly improved in quality and packaging
enhancements, making them comparable to the national brands. The comparability of
private label quality in these categories is also reinforced by another survey that asks
consumers about their perception of quality premium that national brands offer relative to
private labels (Sethuraman and Cole 1997). This study finds consumers are willing to pay
a price premium for national brands even though they are aware that the price premiums
do not reflect corresponding quality differences.
It is important to stress that the label “Dominick’s Finer Foods” is in itself a kind of
branding which differentiates the supermarket chain’s products from true generics. The
very particular sort of branding Dominicks and other supermarket chain makes no attempt
to provide the utility-yielding associations that is the object of much national advertising.
It may, however, do a very good job of assuring physical quality. Fitzell( 1998, p. 126),
states that “Private label owners did not compromise on quality because they could not
afford to put a store name or their own brand name on a product that would be noted as
inferior”. The private label manufacturers association web site also echoes this sentiment.
It states, “Store brands consist of the same or comparable ingredients as the national
brands and because the store's name or symbol is on the package, the consumer is assured
that the product is manufactured to the store's quality standards and specifications.” Use
of name such as Dominick’s serves a bonding function: if one good (or the services of
one store) proves to be dangerous or unpalatable, there is a spillover on the credibility of
all goods and all stores carrying that label.
Finally, we can use Hoch and Banerji’s private label quality ratings to identify
categories where quality differences are more likely so that we can learn whether the
quality differences are likely to be related to lower variable costs or not. To that end we
did further study of the two product categories that were lowest on Hoch and Banerji’s
survey that were also available from the Dominick’s data, toilet paper and soft drinks.
Toilet Paper
This was one of the lowest rated categories in terms of quality comparability. Thus
the higher markups may, in this category, represent true input quality differences and
therefore differences in marginal costs. We were fortunate enough to have a recent
consumer reports on toilet paper, and a recent economic article by Hausman (1999) on the
category as well. Both of these, as well as a survey of consumer perceptions by
Sethuraman and Cole (1997), reinforced the belief that this category does indeed have
significant quality variation. The consumer reports article reported studies of many
products that ranged broadly from ultra plush Charmin to low quality private labels
products and Scott tissue. Hausman (1999) echoes the claim that some brands are of low
quality while others are of high quality. And Sethuraman and Cole (1997) find that
consumers rate toilet paper as one of the two product categories for which the quality gap
as perceived by consumers is highest. Further, Hausman (1999) suggests that this is due to
real differences in input quality in the pulp used to make the paper, which is likely to lead
to higher costs for higher quality branded manufacturers in this category. We thought this
might allow us to compare the private label Scott, but Scott turns out to have many more
sheets per role than the private label, making it possible that Scott faces higher costs
because of the additional sheets, even if the input costs are the same or lower. In the end
this additional information led us to drop the toilet paper category from our paper (even
though the markups in the category averaged above 2.0). We were not able to find
national brand/private label pairs that were of comparable quality and were sure to be the
same or lower cost for the national brand to produce.
Soft Drinks
According to our quality experts, soft drinks are one of the least comparable in terms of
quality based on quality control manger’s perceptions. To the degree that the quality
differences relate to cost savings for the private label, this would inflate our markup
estimates. Yet to the degree that the differences in quality are in terms of taste or other
inputs into the syrup to make the soft drinks, then it is unlikely to relate to substantial
differences in costs. Unlike toilet paper, we decided to keep soft drinks in this paper
because we felt the sources of quality differences we not likely to be related to the
marginal costs faced by soft drinks manufacturers. In this category the majority of the
costs are bottling and distribution. The cost of the syrup is only a very small proportion of
the cost of producing soft drinks.
Types of Private Label Manufacturers
The second issue our field work suggested was that national brand manufacturers
would be able to produce similar quality products at the same or lower prices than private
label manufacturers. To check this we started at the web page of the Private Labels
Manufacturers Association asserts that private label manufactures fall into four
classifications. They are:
1) Large national brand manufacturers that utilize their expertise and excess plant capacity
to supply store brands.
2) Small, quality manufacturers who specialize in particular product lines and concentrate
on producing store brands almost exclusively. Often these companies are owned by
corporations that also produce national brands.
3) Major retailers and wholesalers that own their own manufacturing facilities and provide
store brand products for themselves.
4) Regional brand manufacturers that produce private label products for specific markets.
Clearly in (1) the branded manufacturer has similar variable costs because it uses the
same production facilities and comparable products. To the degree that private labels
come from sources like (1), branded manufacturers using the same plant, and they produce
essentially identical products with the same inputs, it seems reasonable to assume that the
variable costs are likely to be the same. This is not uncommon in the grocery industry. The
first firm to do this was Borden in the pasta category (Fitzell, 1998). There are many
branded manufacturers doing this with products in our sample as well. The scanner data
set does not identify them, and at the present time we have not been able to identify which
national brand/private label pairs are produced by the same manufacturer. But if we are
able to identify such products we will report them as such in future drafts of the paper.
In (2), those smaller manufacturers who are owned by corporations that also produce
national brands are likely to share the same productions expertise and processes making it
reasonable to assume similar production costs for comparable products. In (3) the costs of
production are likely to be the same or higher for private label producers because they do
not produce the product in the same scale as nationally branded products. Supermarket
chains in the United States are regional, limiting the size and scale they can achieve
relative to “national” brands that sell in all of the major supermarket chains.
That leaves us with (4) the regional brands and some of (2) manufacturers who are
not owned by nationally branded manufacturers. Essentially because of the scale and
negotiation power of branded manufacturers, they are able to produce the products at the
same, or more likely lower prices than store brands. National brands have purchasing
power for raw ingredients, packaging materials, etc.
In general, private label manufacturers are smaller, more regional and more
fragmented than their nationally branded counterparts. For example, Fitzell (1998, p.126)
states that “In the evolution of private label into different product categories, the trend in
the United States was more toward smaller manufacturers/processors, leaving the national
brand business, with its high costs of product development and marketing, to the larger
manufacturers.” As another example consider a TOPCO pamphlet which describes its
buying programs [TOPCO handles distribution for what is perhaps the largest generics
program in the country] states that although some of its “sources are large enough to
produce and market products successfully under their own brands In many cases,
however, they are small and medium sized producers who do not have the financial
strength or organization to market their own brand products effectively in competition
with giant competitors.” (Fitzell 1998).
This value of size for national brands has been noted in academic research studies as
well. For example, Schmalensee (1978) has shown that national brands benefit from the
substantial economies of scale in production and advertising that accrue through national
distribution in the cereal category. Likewise Brown (199?) has shown that larger buyers
can receive substantial quantity discounts on their purchases.
B. The Marketing Cost Issue
The second major source of differences between national brands and private labels is
in terms of marketing costs. Industry sources indicate that in general private label
manufacturers do far less in terms of R&D, advertising, trade promotion and consumer
promotion than national brands. For example, Fitzell (1998, p.126) states that national
brand businesses have “high costs of product development and marketing”
This leaves us with the remaining question of how large these costs are and whether
they are fixed or variable costs in nature. We argue that R&D is a fixed cost, and that
national advertising is predominantly a fixed cost. This leaves trade promotion spending
and consumer promotion spending as possible variable cost differences we must consider.
Notice that the largest effect of both trade promotions and consumer promotions is the
reduced price the manufacturer receives from the promotions. Thus they aren’t marginal
cost differences, but adjustments to the prices the manufacturer receives that we must
consider. There are additional costs of implementing the promotional programs that we
should also consider.
Research & Development
R&D is one area where private labels and national brands differ substantially. Fitzell
(1982) states that “private label manufacturers budgets for research and development,
however, usually fall far short of the national brand manufacturers”. While managers of
national brands see these kinds of expenditures as critical to maintaining their brand
equity. Quelch and Harding state that "Brand equity – the added value that a brand-name
gives to the underlying product – must be carefully nurtured by each successive brand
manager. Managers must continually monitor how consumers perceive the brand.
Consistent, clear positioning – supported by periodic product improvements that keep the
brand contemporary without distorting its fundamental promise – is essential. For
example, Proctor and Gamble Company has made 70 separate improvements to Tide
laundry detergent since its launch in 1956, but the brand's core promise that it will get
clothes cleaner than any other product has never been compromised. Consistent
investment in product improvements enhances a brand's perceived superiority … ".
Clearly R&D spending for new product development is not marginal for products being
sold in grocery chains. According to Monroe (1990), as well as many other authors,
research and development costs "do not vary with the (sales) activity level" and are "not
easily traceable to a product or segment" and thus should be treated as fixed from our
perspectives.
Advertising
Advertising spending is another major difference between national brands and private
labels. National brands invest substantial amounts of money in advertising. For example, in
the Survey of Leading National Advertisers in Advertising Age magazine (2000), they
report that advertising spending for major brands is substantial. Futher, many brands have
been doing this for many years. "The strongest national brands have built their consumer
equities over decades of advertising … " (Quelch and Harding, 1996). In fact, these
authors go on to state that restrictions on television advertising help explain the strength
of private labels in Europe relative to in the United States - “Of course, the reasons for the
strength of private labels in Europe are partly structural. First, regulated television
markets mean that cumulative advertising for name brands has never approached U.S.
levels" (Quelch and Harding, 1996).
This has not been true for most private labels. "Private label owners could not afford
the expense of building their own brand equity through multi-million dollar advertising
campaigns”(Fitzell 1998). In particular, for the retailer we are studying they did not invest
anywhere near these amounts, even on a per unit sold or sales basis, on advertising to
build brands.
The question then is whether it is more reasonable to treat advertising expenditures by
manufacturers as a fixed cost or variable cost. If we suppose for a moment that the
branded variant is heavily advertised while the private label version is not, the average cost
of a unit sold (which includes costs incurred by the "marketing department" in addition to
those of the "production department") would be higher for the branded product. The
question then becomes whether advertising should be seen as a marginal cost (as opposed
to a fixed or sunk cost).
The best evidence we could find on this question in the literature is from the Cox
Annual Survey of Promotional Practices (1996). It surveys consumers, packaged goods
manufacturers and grocery retailers on issues on promotion practice and usage.
Specifically "the packaged goods manufacturer questionnaire was sent to 136 executives,
yielding thirty-two usable replies, for a completion rate of 24%. Fact gathering was
conducted from September 5, 1995 through November 17, 1995. The distribution of the
packaged goods manufacturer responses, based on self-reported major company product
category, is as follows: foods, 59%; household products, 3%; soft drinks and candy, 6%;
health and beauty care, 21%; drug and remedies, 3% and other 8%. Of the respondents,
34% represent larger firms/divisions (annual sales = $1 billion plus) and 66% are smaller
firms/divisions (annual sales = less than $1 billion)."
When asked about national advertising, they state that they view their advertising
expenses as mostly aimed at building brand equity, which is more of a fixed or long run
cost. In 1995 packaged goods manufacturers believe that at least 66% of their advertising
spending was meant to build their brand equity only. Of the remaining 34%, 14% was both
brand equity and consumer promotions, 7% was both brand equity and trade promotions,
and the remaining 13% was brand equity, trade and consumer promotions. So we might be
able to argue that up to 80% of advertising is related to brand equity (since it is part of all
answers). Specifically they asked packaged goods manufacturers the "share of media
advertising programs used to support/build brand equity, consumer and trade
promotions".
There are academic authors in this area who also believe that advertising by national
brands is a fixed, rather than variable, cost. Morton and Zettelmeyer (2000) state that
there is a "difference in fixed costs between national and store brands. The advertising
required to support national brands implies that national brand manufacturers have
average costs that are substantially higher than their marginal costs of production."
Trade Promotions
Manufacturers also invest heavily in trade promotions. In the Cox survey they report
some industry averages on how firms in the grocery industry allocate their promotional
dollars. It looks to be about 50% trade promotions, 25% national advertising and 25%
consumer promotions. So trade promotions are the largest component of manufacturer
spending. Private label manufacturers do not undertake nearly as much trade spending, so
this is another major difference between national brands and private labels.
Fortunately the Dominick’s data already incorporates some of the trade spending in
its wholesale prices, so we have already taken part of manufacturer’s trade promotion
spending into account in our estimates of national brand markups. It is likely that there are
trade promotions that are not captured in the wholesale prices in our data. These are most
likely lumpy payments such as slotting allowances, cooperative advertising allowances,
and various case discounts and spiffs the manufacturer gives to the retailer. To the degree
that they are lumpy, and not incorporated into the wholesale price that retailers are using
in their pricing decisions, however, it is not clear that these expenses are truly variable. So
these unreported trade expenditures may not be as relevant as the trade promotions
incorporated into the data we use in this paper. But to the degree that the unreported
trade spending is variable, and substantial, our measure of markups will be overstated.
Consumer Promotions
This is also a major difference between national brands and private labels. Private
labels tend to not coupon or promote to consumers. While branded manufacturers spend,
on average, 25% of their promotional expenses on consumer promotions. That is about on
par with the amount spent on national advertising.
These activities are likely to be either reductions in the price manufacturers receive
(as with redeemed coupons) or variable expenses to run the promotion. Although scanner
data sets often include measures of coupon use, that is not true in this data set. Thus our
data has not taken these price reductions or expenditures into account at this time. We are
trying to get information on consumer promotions by category or product wherever
possible so that we can factor this into our measures of markup. To give the reader some
sense of how important these may be by category, we report the percentage of sales made
using a coupon for all the product categories in our paper in exhibit 2.
Exhibit 2
Product Category
% Dollars with Manufacturers Coupon
Analgesics
10.6
Toothbrushes
12.5
Frozen Juices
1.7 – 5.9
Cereals
16.5
Oatmeals
9.9
Crackers
0.8 – 5.3
Cheeses
2.6 – 6.6
Frozen Entrees
2.5 – 16.5
Canned Tuna
0.6
Fabric Softeners
14.2 – 16.3
Bottled Juices
0.7-2.1
Laundry Detergents
14.0
Snack Crackers
6.4
Cookies
3.9
Grooming Products
9.4
Dish Detergents
12.3
Toothpastes
13.6
Canned Soup
6.5
Bathroom Tissues
4.8
Soft Drinks
2.2
th
*From Supermarket Business 16 Annual Product Preference Study
In sum, we believe there is enough evidence to suggest that using private label prices
to infer national brand costs is a reasonable assumption in this industry. We are in the
process of gathering additional evidence at a category and product level to check this
assumption further, but there is reason to believe that this measure of markup can be
appropriate for at least some categories and products in this industry. Further, since the
private label will have some markup, and the nationally branded products have advantages
on size and scale in production, packaging and negotiation on input prices we believe the
use of private labels may actually be a conservative measure of these costs.
III. Data
The scanner data come from Dominick's Finer Food (DFF), which is one of the
largest retail supermarket chains in the larger Chicago metropolitan area operating 94
stores.
Large multi store U.S. Supermarket chains of this type made up about
$310,146,666,000 in total annual sales in 1992, which was 86.3% of total retail grocery
sales (Supermarket Business, 1993). In 1999 the retail grocery sales has reached $435
billion (Chevalier, Kashyap, and Rossi, 2000). Thus the chain we study is a representative
of a major class of the retail grocery trade. Moreover, Dominick’s type multistore
supermarket chains’sales constitute about 14 percent of the total retail sales of about
$2,250 billion in the US. Thus the market we are studying has a quantitative economic
significance as well. ((Since retail sales account for about 9.3 percent of the GDP, our
data set is a representative of as much as 1.28 percent of the GDP, which seems
substantial.))
The data consist of up to 400 weekly observations of actual transaction prices in 29
different categories, covering the period from September 14, 1989 to May 8, 1997. The
data come from the store scanner data base which contain actual retail transaction prices
of the products along with profit margin the supermarket makes on each one of them.
From the information on retail prices and the profit margin, we have constructed the
weekly time series of wholesale prices.
The retail prices are the actual transaction prices: the price customers paid at the
cash register each week. If the item was on sale, then the price data we have reflects the
sale price. Although the retail prices are set on a chain-wide basis at the corporate
headquarters of Dominick’s, there may still be some price variation across the stores
depending on the competitive market structure in and around the location of the stores.
For example, if a particular store of the chain is located in the vicinity of a Cub Food
store, then the store may be designated a “Cub-fighter” and as such, it may pursue a more
aggressive pricing policy in comparison to the stores located in other zones. The data we
use are averaged across the stores of this chain.5
The wholesale price series, which measure the direct cost to the retailer, are computed by
combining the retail price data with the information provided by the retailer on their
weekly gross margins for each product and using the relation, wholesale price = (1 – gross
margin %) multiplied by the retail price. The wholesale price DFF uses for computing their
gross margin series is constructed by the retailer as a weighted average of the amount the
retailer paid for all their inventory. For example, a profit margin of *25.3 means that DFF
makes 25.3 cents on the dollar for each item sold which yields a cost of good sold of 74.7
cents. If the retailer bought its current stock of a Kellog’s Corn Flakes, 18oz, in two
transactions, then its wholesale price is computed as the average of these two transaction
prices (no FIFO or LIFO accounting rules are used in these computations).6
For the purpose of this study, we had to go through the entire DFF’s data set and
identify pairs of national brand and private label products. Of the approximately 350 pairs
we were able to locate in the 29 product categories, we have eliminated a portion of them
because of substantial size differences. For example, if, say, in cereals category we
compare Kellog’s Corn Flakes to DFF’s Corn Flakes, but the national brand comes in 32
oz box (which is a family size) while DFF’s product comes in 18 oz box, then this is not a
good comparison since the two products are not really comparable as they are targeted to
two different kinds of customers, and computing prices per oz would not eliminate this
fundamental problem. Other pairs were eliminated because many non-private label brands
5
Our retail prices reflect any retailer’s coupons or discounts, but do not include manufacturer
coupons. Further, none of these product categories are not used by Dominick’s as loss-leaders.
6
Thus, the wholesale costs in the data do not correspond exactly to the replacement cost or the
last transaction price. Instead we have the average acquisition cost (ACC) of the items in inventory. So the
supermarket chain sets retail prices for the next week and also determines AAC at the end of each week, t,
according to the formula
AAC(t+1) = (Inventory bought in t) Price paid(t) + (Inventory, end of t-l-sales(t)) AAC(t)
There are two main sources of discrepancy between replacement cost and AAC. The first is the familiar
one of sluggish adjustment. A wholesale price cut today only gradually works itself into AAC as old,
higher priced inventory is sold off. The second arises from the occasional practice of manufacturers to
inform the buyer in advance of an impending temporary price reduction. This permits the buyer to
completely deplete inventory and then "overstock" at the lower price. In this case AAC declines
did not really qualify as national brand products as these products are marketed only
regionally (and some even locally only) or they did not have substantial market share. Still
other pairs were eliminated because of our uncertainty about equality of their quality.
Thus, the results we are reporting in the paper are for product pairs, such that (1) the
national brand product is clearly marketed nationally, (2) the national brand products are
widely recognized, (3) the national brand products have non-trivial market share, and (4)
the pair of national brand – private label products are comparable in size and quality, as
much as possible.
The product pairs that pass these criteria represent 19 categories which include
Analgesics, Bottled Juices, Cereals, Cheeses, Cookies, Crackers, Canned Soups, Dish
Detergent, Frozen Entrees, Frozen Juices, Fabric Softeners, Grooming Products, Laundry
Detergent, Oatmeal, Soft Drinks, Snack Crackers, Toothbrush, Tooth Pastes, and Canned
Tuna.7
To compute the average markup figures for each category , which are reported in
Tables 1–3, we had to compress the data by three different procedures of averaging. First,
we have averaged all weekly price series across all the chain's stores to get a single weekly
wholesale and retail price series for each of the national brand and private label products
chosen for the analysis. This averaging was done by weighing the national brand and
private label price series from each store according to the store's sales share in the total
DFF's sale where the sales are measured by the weekly sales figures of the specific national
brand and private label products, respectively. Since the scanner database does not include
information on the quantities purchased at the wholesale level, we used the retail sales
figures as its proxy. This procedure likely introduces a noise in the generated series
because the retail sales are more spread over time in comparison to wholesale purchases
which likely occur with lower frequency. The noise, however, will mostly affect the
weekly volatility properties of the price series, but the average values are unlikely to be
precipitously to the lower price and stays there until the large inventory acquired at that price runs off.
Thus, the accounting cost shows the low price for some time after the replacement cost has gone back up.
7
Thus, in the remaining ten categories, which include Bath Soap, Beer, Cigarettes, Front-EndCandies, Frozen Dinners, Paper Towels, Refrigerated Juices, Shampoos, Soaps, and Bathroom Tissues, we
were unable to find comparable national brand-private label pairs.
affected from this procedure in a significant way. The purpose of the weighing procedure
we have implemented is to ensure that the price series coming from the stores that sell
proportionally more than others, receive higher weight.
Next, we computed the weighted average weekly values of the above across-store
weighted averaged series by taking each price series for the sample period it was available
and computing its weekly average value by weighing each weekly observation according
to the share of that week’s quantity sold in the total quantity sold over the entire sample
period. As before, the purpose of this weighing is to give higher weight to observations
(i.e., weeks) that represent higher sales volume measured in terms of products’quantity
(such as oz’s). In each case the prices of national brand products were weighed using the
sales volume of that specific national brand product while the price series of the private
label products were correspondingly weighed by sales volume of the private label
products. These series then were used to compute various markup measures reported in
Tables A1.1–A19.2.
It should be noted that an alternative way of computing these weekly average markup
values for each national brand-private label product pair is to first compute weekly markup
series for the entire sample period covered by each product pair and then compute their
weekly weighted average using the procedure outlined above. Preliminary calculations
performed using this procedure has so far yielded similar quantitative results in terms of
average markup figures. This procedure, however, has the advantage that by first
computing markups, that is, first computing ratios and then averaging them over time
(instead of first averaging them over time and then computing the ratios) makes it possible
to explore the time series variability in each individual markup series and perhaps also to
provide some measure of over time variability associated with the markup. We are
currently performing these calculations and the next revision of the manuscript will report
the results.
Finally, we have taken the above-calculated average markup figures for each
product pair and computed the average markup for each of the 19 product categories
included in our sample. As before, these category averages were also calculated as
weighted averages. However, unlike the previous steps, here the weighing was done
according to the share of the dollar value of the sales for each product pair in the dollar
value of the total sales in the category. For example, if in the analgesics category we have
22 national brand-private label product pairs, to compute the category average markup,
we took the markup figures for the 22 product pairs (listed in Table A1.1) and computed
their weighted average, where the weights are the ratios of the total dollar sales of the pair
to the total dollar sales in the category. The weights here use dollar sales rather than unit
sales in order to avoid the problem of “adding apples to oranges.” The resulting category
averages figures are reported in Tables 1–3.
IV. Results
The most unique aspect of our findings is that we can back out the wholesale prices
paid by the retailer to manufacturers. This allows us to get a measure of markups for
national brands based on the wholesale prices they receive from retailers. We report the
results from these studies first in section IV.1. Then we report the retail markups on both
national brands and private labels in section IV.2. Finally, in section IV.3 we present the
markups for national brands had we used final retail prices, and discuss the advantages and
disadvantages of using this as an estimate of markups based on lessons from our study.
IV.1 Markup Ratios based on wholesale prices
As seen by Table 1, the markups based on wholesale prices are generally large. These
markup ratios are calculated by dividing the wholesale price of the national brands with
the wholesale price of the comparable private label. For the product categories of
analgesics, toothbrushes, and crackers the markups are higher than 2. This pushes the
markup ratios to the range of substantial market power for national brands in these
categories by Hall's (1986) definition. There are also a couple of product categories that
are near 2, grooming products and fabric softeners. The rest of the product categories fall
in the range of 1.4 to 1.6, which is some market power according to Hall (1986). These
include oatmeal, cereals, bottled juices, cookies, frozen juices, canned soups, snack
crackers, laundry detergents, soft drinks, dish detergents, and toothpaste. The remaining
four categories cheeses, canned tuna, laundry detergent and frozen entrees are in the range
of 1.2 to 1.3.
It is interesting to note that our estimates for ready-to-eat breakfast cereals are very
close to the price-cost margin of 50% found by Hausman (1997) using a sophisticated
demand elasticity approach. Evidence from private label prices is consistent with the
interpretation of branded breakfast cereals, along with a number of other heavily promoted
products, as highly differentiated products with low demand elasticities.
There are examples of large markups by brand within some categories that are
interesting to consider. Tables A1 to A19 give the results by national brand/private label
pair we report in the study. For example, looking at the specific markups by brand and
type of soda we observe some interesting patterns. In the cola category we find that Coke
and Pepsi both have markups near 2, averaging 1.9. While Royal Crown Cola has markups
averaging 1.7, which is closer to the category average of 1.68. Thus, the more heavily
branded and well known products are receiving higher markups in the category. Similarly
for brands in the tonic water types of products, Schweppes, Seagrams and Canada Dry has
markups of 1.82, 1.9 and 2.48 respectively. In analgesics we found the highest markups
for children’s aspirin. In the Toothbrush category we see the highest markups for Reach
and Crest, which are leading national brands. Followed by Pepsodent and Johnson &
Johnson which are the next strongest brands, also receiving markups over 2, but still less
than the Reach and Crest.
Taken as a whole we see a great deal of evidence that there can be substantial
wholesale markup ratios for nationally branded products in this industry. In category after
category, brand after brand, we tend to find markups at least as high as 1.3 and more often
in the 1.4 to 1.6 range. And we find many brands that are able to command markups of
nearly 100% in many categories.
IV.2 Retail markup ratios for private labels and national brands
Table 2 shows the retailer’s markups for the private labels and national brands by
category. We measured retail markup as the retail price of the product divided by the
wholesale price of the product. Two themes seem to emerge from this table. First, in
almost every category the retail markups are higher for private labels than national brands.
Second, retail markups are generally lower for nationally branded products than nationally
branded markups based on our estimates.
An examination of Table 2 shows that the retailer’s markups for national brands range
from 1.03 (cereals and laundry detergent) to 1.38 (toothbrushes). There are many
products with markups less than 1.1, including the categories of analgesics, fabric
softeners, dish detergents, and oatmeal. Most of the other categories fall below markups
of 1.2, including the categories of bottled juice, cheese, cookies, crackers, toothpaste
grooming products, frozen entrees, and canned tuna. The retailer’s markups for private
label products are substantially higher, ranging from 1.07 in laundry detergents to 3.83 in
toothbrushes. Only dish detergents, cereals and frozen entrees are below 1.2, the rest are
higher and tend to be in the range of 1.2 to 1.5.
Comparing the rows in Table 2 we see that the retailer’s markups for private labels
are higher than their markups for national brands in every category except frozen entrees.
In most categories the markup is higher by somewhere between .1 and .2. In some
categories it is even higher, about .3 in analgesics and crackers, and much larger for
toothbrushes. Thus we offer clear evidence that retailer’s markups are higher for private
labels than national brands. This fact is well known in the trade. "The gap between
marginal and average cost of national brands allows retailers to achieve higher price-cost
margins than those earned with national brands. Industry observers, the popular press and
academic work all indicate that this effect can be quite large" (Morton and Zettelmeyer,
2000). Hoch and Banerji (1993) state that "Industry sources suggest that retailer gross
margins on private labels are 20% to 30% higher than on national brands." This is also
consistent with differences between the United States and Europe. "In European
supermarkets, higher private-label sales result in higher average pretax profits. U.S.
supermarkets average only 15% of sales from private labels, they average 2% pre-tax
profits from all sales. By contrast, European grocery stores such as Sainsbury's, with 54%
of its sales coming from private labels, and Tesco, with 41%, average 7% pretax profits."
(Quelch and Harding, 1996)
Comparing Table 2 with Table 1 we see that the retailer’s markups in each category
are lower than the manufacturer’s markups in every instance. For example, even in the
case where nationally branded markups are low, such as canned tuna (1.23) and cheese
(1.31), the corresponding retail markups are 1.14 and 1.17 respectively. The contrasts can
be very large, with nationally branded markups being double or triple the markups of
retailers for the same product.
IV.3 Markup Ratios Based on Retail Prices
Our original inspiration for using scanner data to study markups was based on the
idea of using retail prices to infer markups for national brands. Anyone who walks the
aisles of a supermarket and looks at the prices of national brands and private labels is sure
to see some combinations which suggest that national brands must have substantial
markups. Our most vivid example had one author buying cold remedies at the grocery
store and being stunned by the markups for chemically identical offerings. Further, the
authors who had suggested this approach in the past (Scherer 1980; Carlton and Perloff
1994) had focused on using retail prices to infer markups.
The value of these estimates of markups is that retail prices are becoming more and
more available with new technologies in computers, software, scanning and other systems
being developed. Any markets where prices are posted or price data is systematically
collected offers the possibility of using these kinds of measures to infer markups for
nationally branded products. Further, this kind of price data is already public, so it is easier
to gain access to. To get wholesale prices requires that the retailers give information on
their costs or margins. Usually, wholesale price information is not part of publicly available
scanner data sets. Most firms prefer to keep their margins private and proprietary. One of
the unique advantages of the Dominick’s dataset is that the retailer in willing to share their
margin, and therefore cost, data. Given the proprietary nature of costs and margins, it is
important to assess how well markup estimates based on posted prices work as estimates
of markups.
Table 3 shows the markups for national brands in 19 categories based on the retail
prices of nationally branded products and private labels. The markup estimates range from
a high of 2.36 in toothbrushes to a low of 1.16 for canned tuna. The majority of the
markups are below 1.4, with the only exceptions being cereal (1.45), razors (1.58),
analgesics (1.64), fabric softeners, crackers (1.71) and cookies as well as the
aforementioned toothbrushes. Overall, based on Hall’s ratings (1986), we would suggest
there was some market power but not substantial market power in this data based on
markups estimated from retail price data alone.
In Figure 1 we report the markups in Table 1 and Table 3 together. Two insights
emerge from figure 1. First, the markups based on wholesale prices are significantly larger
than the markups based on retail prices. In general the markups increase by about .2 or
more, depending on the product category. The increase is even larger in analgesics,
crackers, grooming, and toothbrushes.
The reason this occurs is that the retailer takes larger markups on private labels than
on national brands, so that the retail prices understate the manufacturer markups in this
industry by combining the pricing decision of both the retailer and the manufacturers in
this measure. This suggests that one criterion for using retail prices to infer markup is that
retailers have small markups in general to minimize this bias. Or that retailers have more
uniform policies for markups on both national brands and private labels than in this
industry.
Also notice that the general order of which category has the highest markups is
maintained estimating markups using retail prices rather than using wholesale prices. The
highest markup categories such as analgesics are high using both measures. To the extent
that the research question is about variation between markups rather than the absolute size
of markups, this suggests that using retail prices may be appropriate for studying those
questions.
Overall, to the degree that the private label products are comparable, the
differentiation between them and nationally branded products are based on fixed costs
such as advertising or R&D, and the retail markups are small these may be a very useful
proxy for markups in an industry. But the researcher should keep in mind that the retail
markups are lower, so they may understate the markups in this industry.
VI. Discussion and Conclusions
In this paper we have investigated the size of markups for nationally branded products
sold in the U.S. retail grocery industry. Our approach, which we hope will serve as a
complement to more structural econometric approaches, treats the wholesale price of the
comparable private label product as an upper bound on the marginal costs faced by the
branded manufacturer. Using scanner data from a large Midwestern grocery chain, we
have estimated the markup ratios for over 200 products in 19 categories. We found that
markup ratios measured this way range from 2.5 for crackers and 2.3 in the analgesics
category to 1.2 in canned tuna, with the majority of categories in the range 1.4 to 1.7.
Our numbers are on the high side of, though consistent with, those in the existing
literature.
Our approach offers several benefits. Because it involves only a simple computation
(once the data have been assembled), the method permits calculation of markups for a
large variety of products. It is transparent and intuitive, and it offers a benchmark
comparison for more structural approaches.
Particularly in light of the importance of markups in recent macroeconomic discourse,
one might ask whether the finding of high markups for heavily advertised differentiated
products generalizes to the economy at large. In this direction, it is worth noting that even
some “commodity” products such as aluminum and other producers’goods come in both
branded and generic versions, and that the price gap for those products is comparable to
that for the supermarket goods we have studied. This is also true for other consumer
goods sold outside the supermarket industry, home and office supply products would be
one example.
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Table 1. Average National Brand Markups Based on Wholesale Prices
Product Category
Average Markup
Tooth Brushes
7.93
Crackers
2.53
Analgesics
2.34
Grooming Products
1.92
Fabric Softeners
1.77
Soft Drinks
1.68
Cookies
1.67
Oatmeals
1.55
Canned Soups
1.53
Cereals
1.49
Snack Crackers
1.49
Toothpastes
1.46
Dish Detergents
1.41
Frozen Juices
1.41
Bottled Juices
1.40
Cheeses
1.31
Laundry Detergents
1.26
Canned Tuna
1.23
Forzen Entrees
1.22
Table 2. Average Retailer Markups on National Brand and Private Label
Average Markup on
National Brand
Average Markup on
Private Label
Tooth Brushes
1.38
3.83
Crackers
1.14
1.47
Analgesics
1.06
1.36
Grooming Products
1.12
1.37
Fabric Softeners
1.06
1.21
Soft Drinks
1.29
1.48
Cookies
1.13
1.30
Oatmeals
1.09
1.38
Canned Soups
1.29
1.43
Cereals
1.03
1.17
Snack Crackers
1.23
1.40
Toothpastes
1.12
1.28
Dish Detergents
1.07
1.14
Frozen Juices
1.31
1.46
Bottled Juices
1.13
1.23
Cheeses
1.17
1.29
Laundry Detergents
1.03
1.07
Canned Tuna
1.14
1.20
Forzen Entrees
1.18
1.15
Product Category
Table 3. Average National Brand Markups Based on Retail Prices
Product Category
Average Markup
Tooth Brushes
2.36
Crackers
1.98
Analgesics
1.72
Grooming Products
1.57
Fabric Softeners
1.56
Soft Drinks
1.45
Cookies
1.44
Oatmeals
1.24
Canned Soups
1.38
Cereals
1.32
Snack Crackers
1.24
Toothpastes
1.26
Dish Detergents
1.32
Frozen Juices
1.28
Bottled Juices
1.29
Cheeses
1.19
Laundry Detergents
1.20
Canned Tuna
1.16
Forzen Entrees
1.26
Table A1.1. Analgesics: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
MOTRIN IB CAPLETS
1.61
1.46
MOTRIN IB
1.07
0.95
MOTRIN IB GELCAPS
1.89
1.63
TYLENOL INFANT DROPS
2.08
1.71
TYLENOL X/S CAPLET
2.75
2.19
TYLENOL X/S GELCAPS
1.90
1.73
CHILD CHEW GRAP TYLENOL
1.79
1.37
CHILD CHEW FRT TYLENOL
1.79
1.38
TYLENOL TABLETS REGULAR
2.35
1.86
TYLENOL X/S TABLETS
1.82
1.57
TYLENOL X/S TABLETS
1.16
1.01
TYLENOL X/S TABLETS
1.15
1.00
ADVIL
1.86
1.64
ADVIL CAPLETS
1.46
1.32
ANACIN-3 CHILDREN TABS
7.63
3.77
BAYER CHILD ASPIRIN
3.23
1.81
PANADOL CHILD TABS
6.73
3.51
EXCEDRIN IB TABS 50
1.94
1.67
EXCEDRIN IB TAB 100
1.51
1.39
EXCEDRIN IB CAPLETS
1.81
1.64
EXCEDRIN IB TABS 50
2.00
1.70
ALEVE CAPLETS
1.89
1.63
Weighted Average
2.34
1.72
Product Pair
Table A1.2. Analgesics: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
MOTRIN IB CAPLETS
1.02
1.12
MOTRIN IB
1.09
1.22
MOTRIN IB GELCAPS
1.04
1.21
TYLENOL INFANT DROPS
1.07
1.31
TYLENOL X/S CAPLET
1.06
1.32
TYLENOL X/S GELCAPS
1.02
1.12
CHILD CHEW GRAP TYLENOL
1.13
1.47
CHILD CHEW FRT TYLENOL
1.13
1.47
TYLENOL TABLETS REGULAR
1.02
1.28
TYLENOL X/S TABLETS
1.01
1.17
TYLENOL X/S TABLETS
1.03
1.19
TYLENOL X/S TABLETS
1.03
1.18
ADVIL
1.03
1.17
ADVIL CAPLETS
1.02
1.12
ANACIN-3 CHILDREN TABS
1.09
2.20
BAYER CHILD ASPIRIN
1.23
2.20
PANADOL CHILD TABS
1.14
2.20
EXCEDRIN IB TABS 50
1.06
1.24
EXCEDRIN IB TAB 100
1.03
1.13
EXCEDRIN IB CAPLETS
1.05
1.16
EXCEDRIN IB TABS 50
1.06
1.24
ALEVE CAPLETS
1.05
1.21
Weighted Average
1.06
1.36
Product Pair
Table A2.1. Bottled Juice: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
MOTTS APPLE JUICE
2.10
2.08
SENECA APPLE JUICE
1.88
1.42
GATORADE ORANGE DRIN
1.83
1.72
NORTHERN CRAN/RASP
1.64
1.50
FLAVOR FRESH APPLE J
1.58
1.14
NORTHERN CRAN/RASP
1.55
1.47
TREE TOP APPLE JUIC
1.47
1.14
MUSSELMAN APPLE JUIC
1.46
1.13
MM NATL. APPLE JUIC
1.45
1.10
O S RUBY RED GRAPEF
1.43
1.25
O S CRANRASPBERRY DR
1.42
1.33
O S PINK GRAPEFRUIT
1.41
1.31
O S GRAPEFRUIT JUICE
1.37
1.26
NORTHLAND CRANBERRY
1.35
1.38
NORTHLAND CRANBERRY
1.34
1.38
NORTHLAND CRANBERRY
1.33
1.37
SPEAS FARM APPLE JUI
1.31
1.08
WELCH'S GRAPE JUICE
1.24
1.22
O S CRANBERRY JUICE
1.23
1.21
SUNSWEET PRUNE JUICE
1.19
1.13
VERYFINE R/RED GRPF
1.17
1.12
VERYFINE CRANBERRY
1.13
1.16
DEL MONTE PRUNE JCE/
1.00
1.08
Weighted Average
1.40
1.29
Product Pair
Table A2.2. Bottled Juice: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
MOTTS APPLE JUICE
1.43
1.44
SENECA APPLE JUICE
1.25
1.66
GATORADE ORANGE DRIN
1.26
1.34
NORTHERN CRAN/RASP
1.08
1.15
FLAVOR FRESH APPLE J
1.21
1.68
NORTHERN CRAN/RASP
1.07
1.18
TREE TOP APPLE JUIC
1.19
1.53
MUSSELMAN APPLE JUIC
1.16
1.49
MM NATL. APPLE JUIC
1.12
1.47
O S RUBY RED GRAPEF
1.04
1.20
O S CRANRASPBERRY DR
1.09
1.15
O S PINK GRAPEFRUIT
1.13
1.22
O S GRAPEFRUIT JUICE
1.12
1.22
NORTHLAND CRANBERRY
1.08
1.06
NORTHLAND CRANBERRY
1.09
1.06
NORTHLAND CRANBERRY
1.08
1.06
SPEAS FARM APPLE JUI
1.33
1.62
WELCH'S GRAPE JUICE
1.10
1.12
O S CRANBERRY JUICE
1.04
1.06
SUNSWEET PRUNE JUICE
1.23
1.29
VERYFINE R/RED GRPF
1.15
1.20
VERYFINE CRANBERRY
1.09
1.06
DEL MONTE PRUNE JCE/
1.36
1.25
Weighted Average
1.13
1.23
Product Pair
Table A3.1. Cereals: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
TOTAL RAISIN BRAN
1.79
1.63
KELLOGGS CORN FLAKES
1.57
1.28
KELLOGGS NUT & HONEY
1.54
1.37
POST RAISIN BRAN
1.51
1.40
KELLOGGS RAISIN BRAN
1.48
1.34
APPLE CINNAMON CHERR
1.48
1.31
W.C. X-RAISIN BRAN C
1.46
1.39
KELLOGG'S FROSTED FL
1.44
1.27
KELLOGG FROSTED FLAK
1.41
1.24
KLLG LWFT GRANOLA W/
1.40
1.25
HONEY NUT CHEERIOS
1.38
1.22
Weighted Average
1.49
1.32
Product Pair
Table A3.2. Cereals: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
KELLOGG’S CORN FLAKES
1.04
1.28
KELLOGG’S LWFT GRANOLA
1.09
1.22
KELLOGG’S NUT & HONEY
1.05
1.18
APPLE CINNAMON CHERRIOS
1.03
1.16
HONEY NUT CHEERIOS
1.02
1.16
KELLOGG’S FROSTED FLAKES
0.99
1.15
KELLOGG’S FROSTED FLAKES
1.03
1.15
W.C. X-RAISIN BRAN
1.09
1.15
POST RAISIN BRAN
1.06
1.14
TOTAL RAISIN BRAN
1.05
1.14
KELLOGG’S RAISIN BRAN
1.03
1.14
Weighted Average
1.03
1.17
Product Pair
Table A4.1. Cheese: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
KR SOFT PHILLY CREAM
1.82
1.53
KRAFT COLBY JACK CHU
1.00
0.93
KR PHILA CREAM CHEES
1.53
1.23
KR GRTD PARMESAN
1.32
1.26
$KRAFT SHRED MOZZARE
1.15
1.12
KR MILD COLBY
1.24
1.09
KR LT/NAT SWISS CHUN
1.33
1.21
KR KLN SLICED SWISS
1.30
1.17
KR LT NAT SHRED MOZZ
1.45
1.30
KRAFT HALFMOON MILD
1.24
1.14
~KRAFT SHREDDED MOZZ
1.17
1.15
KR SL COLBY RESEALAB
1.40
1.24
KR SHRED MOZZARELLA
1.17
1.06
KR SL MUENSTER RESEA
1.40
1.28
KR SHRED MILD CHEDDA
1.29
1.17
KRAFT FINELY SHREDDE
1.24
1.13
Weighted Average
1.31
1.19
Product Pair
Table A4.2. Cheese: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
KR SOFT PHILLY CREAM
1.25
1.49
KRAFT COLBY JACK CHU
1.25
1.36
KR PHILA CREAM CHEES
1.20
1.49
KR GRTD PARMESAN
1.09
1.14
KRAFT SHRED MOZZARE
1.05
1.08
KR MILD COLBY
1.19
1.35
KR LT/NAT SWISS CHUN
1.15
1.26
KR KLN SLICED SWISS
1.14
1.27
KR LT NAT SHRED MOZZ
1.19
1.32
KRAFT HALFMOON MILD
1.13
1.23
KRAFT SHREDDED MOZZ
1.13
1.15
KR SL COLBY RESEALAB
1.17
1.31
KR SHRED MOZZARELLA
1.18
1.30
KR SL MUENSTER RESEA
1.18
1.29
KR SHRED MILD CHEDDA
1.19
1.31
KRAFT FINELY SHREDDE
1.18
1.29
Weighted Average
1.17
1.29
Product Pair
Table A5.1. Cookes: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
SALERNO BUTTER COOKI
1.27
1.08
SALERNO CHOC GRAHAMS
1.34
1.18
SALERNO MINT CREAM P
1.53
1.45
SALERNO ROYAL GRAHAM
1.48
1.29
SALERNO OATMEAL PNT
0.96
0.87
SALERNO VANLLA WAFER
1.75
1.44
MINI CHOCOLATE CHIP-
1.37
1.09
SALERNO CHOC CHOC CH
1.83
1.74
SALERNO CHOC CHIP W/
1.83
1.75
SALERNO PREMIER CHOC
1.82
1.73
SUPER MARIO CHOCOLAT
1.43
1.25
KLBR SUGAR WAFERS-VA
1.74
1.40
ARCHWAY CHOC CHIP S
1.08
1.00
ARCHWAY CINN APPLE S
1.42
1.17
ARCHWAY CHOC CHIP &
1.25
1.10
ARCHWAY CHOCO CHIP&
1.56
1.29
ARCHWAY FF FIG BARS
1.41
1.29
ARCHWAY FATFREE AP
1.53
1.49
KEEBLER LF HONEY GRA
1.98
1.54
W.C.CHOC CHIP ALL B
1.78
1.30
HONEY MAID CHOCOLATE
1.29
1.23
ALMOST HOME CHOCOLAT
1.83
1.51
ALMOST HOME OATMEAL
1.78
1.44
NUTTER BUTTER PNT BT
3.40
2.75
CAMEO CREME SANDWICH
3.37
2.72
FAM AMOS CHOC CHIP W
1.98
1.71
FAM AMOS CHOC CHIP C
1.93
1.68
FAMOUS AMOS CHOC CHI
1.25
1.13
FAMOUS AMOS CHOC CRE
1.37
1.22
Weighted Average
1.67
1.44
Product Pair
Table A5.2. Cookes: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
SALERNO BUTTER COOKI
1.18
1.39
SALERNO CHOC GRAHAMS
1.15
1.31
SALERNO MINT CREAM P
1.18
1.24
SALERNO ROYAL GRAHAM
1.14
1.31
~SALERNO OATMEAL PNT
1.25
1.38
SALERNO VANLLA WAFER
1.14
1.39
MINI CHOCOLATE CHIP-
1.08
1.35
SALERNO CHOC CHOC CH
1.13
1.19
SALERNO CHOC CHIP W/
1.13
1.18
SALERNO PREMIER CHOC
1.13
1.19
SUPER MARIO CHOCOLAT
1.17
1.34
KLBR SUGAR WAFERS-VA
1.12
1.39
`ARCHWAY CHOC CHIP S
1.11
1.19
ARCHWAY CINN APPLE S
1.08
1.32
ARCHWAY CHOC CHIP &
1.19
1.35
~ARCHWAY CHOCO CHIP&
1.11
1.35
ARCHWAY FF FIG BARS
1.06
1.16
~ARCHWAY FATFREE AP
1.09
1.11
KEEBLER LF HONEY GRA
1.11
1.43
~W.C.CHOC CHIP ALL B
1.01
1.37
HONEY MAID CHOCOLATE
1.11
1.16
ALMOST HOME CHOCOLAT
1.12
1.35
ALMOST HOME OATMEAL
1.12
1.39
NUTTER BUTTER PNT BT
1.11
1.38
CAMEO CREME SANDWICH
1.12
1.38
FAM AMOS CHOC CHIP W
1.16
1.35
FAM AMOS CHOC CHIP C
1.17
1.35
FAMOUS AMOS CHOC CHI
1.07
1.18
FAMOUS AMOS CHOC CRE
1.09
1.22
Weighted Average
1.13
1.30
Product Pair
Table A6.1. Crackers: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
NAB PREMIUM SALTINES
4.12
3.02
SALERNO SALTINES
2.93
2.33
NAB PREMIUM SALTINES
2.71
2.33
SALERNO SALTINES
2.45
2.09
NAB PREMIUM SALTINES
2.13
1.48
HONEY MAID GRAHAMS-L
1.91
1.52
KEEBLER GRAHAM CRACK
1.73
1.41
NAB GRAHAM CRACKERS
1.65
1.34
SALERNO SALTINES
1.55
1.16
SALERNO GRAHAM CRACK
1.45
1.22
DELUXE GRAHAM BONUS
1.31
1.03
Weighted Average
2.53
1.98
Product Pair
Table A6.2. Crackers: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
SALERNO SALTINES
1.24
1.66
NAB PREMIUM SALTINES
1.15
1.66
NAB PREMIUM SALTINES
1.16
1.58
SALERNO SALTINES
1.26
1.58
HONEY MAID GRAHAMS-L
1.11
1.39
KEEBLER GRAHAM CRACK
1.12
1.37
NAB GRAHAM CRACKERS
1.11
1.37
SALERNO GRAHAM CRACK
1.15
1.37
NAB PREMIUM SALTINES
1.13
1.32
SALERNO SALTINES
1.13
1.32
DELUXE GRAHAM BONUS
1.04
1.32
Weighted Average
1.14
1.47
Product Pair
Table A7.1. Canned Soup: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
C&B CREAM OF MUSHROO
2.57
2.52
PROG CHICKEN RICE W/
1.30
1.24
PROG MINESTRONE SOUP
1.29
1.29
PROG CHICKEN NOODLE
1.31
1.26
PROG VEGETABLE SOUP
1.35
1.29
PROG ZESTY MINESTRON
2.06
1.86
CAMP TOMATO SOUP
1.57
1.10
CHUNKY MINESTRONE SO
1.32
1.26
CHUNKY VEGETABLE
1.35
1.25
CHUNKY CHICKEN NOODL
1.29
1.23
CHUNKY CHICKEN RICE
1.27
1.22
CHUNKY VEGETABLE SOU
1.44
1.32
CHUNKY CHICKEN NOODL
1.83
1.75
HOME COOKIN' TOMATO
1.49
1.42
CAMP CHICKEN WITH RI
1.37
1.19
CAMP CREAM OF CELERY
1.43
1.16
CAMP VEGETABLE BEEF
1.72
1.54
CAMP BEAN W/BACON SO
1.29
1.01
CAMP BROCC CHEESE SO
1.54
1.41
CAMPBELL CHICKEN & S
1.34
1.22
HOME COOKIN MINESTRO
1.27
1.22
SWAN CHIX BROTH
1.45
1.13
HEALTHY REQ. VEGETAB
1.74
1.55
ROKEACH VEGETABLE SO
2.03
1.73
Weighted Average
1.53
1.38
Product Pair
Table A7.2. Canned Soup: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
C&B CREAM OF MUSHROO
1.23
1.25
PROG CHICKEN RICE W/
1.17
1.22
PROG MINESTRONE SOUP
1.30
1.30
PROG CHICKEN NOODLE
1.17
1.22
PROG VEGETABLE SOUP
1.31
1.37
PROG ZESTY MINESTRON
1.19
1.32
CAMP TOMATO SOUP
1.06
1.51
CHUNKY MINESTRONE SO
1.24
1.30
CHUNKY VEGETABLE
1.23
1.33
CHUNKY CHICKEN NOODL
1.17
1.22
CHUNKY CHICKEN RICE
1.17
1.22
CHUNKY VEGETABLE SOU
1.46
1.60
CHUNKY CHICKEN NOODL
1.28
1.34
HOME COOKIN' TOMATO
1.43
1.50
CAMP CHICKEN WITH RI
1.33
1.53
CAMP CREAM OF CELERY
1.29
1.58
CAMP VEGETABLE BEEF
1.30
1.46
CAMP BEAN W/BACON SO
1.43
1.82
CAMP BROCC CHEESE SO
1.28
1.40
CAMPBELL CHICKEN & S
1.30
1.42
HOME COOKIN MINESTRO
1.25
1.30
SWAN CHIX BROTH
1.52
1.96
HEALTHY REQ. VEGETAB
1.34
1.51
ROKEACH VEGETABLE SO
1.42
1.67
Weighted Average
1.29
1.43
Product Pair
Table A8.1. Dish Detergent: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
DAWN LEMON
1.93
1.81
SUNLIGHT AUTO DISH
1.70
1.61
PALMOLIVE AUTO DISH
1.60
1.50
JOY LEMON
1.54
1.43
SUNLIGHT AUTO DISH
1.36
1.30
SUNLIGHT AUTO DISH
1.36
1.30
LEMON DAWN
1.34
1.22
DIAL AUTO DISH DETER
1.32
1.16
SUNLIGHT AUTO GEL
1.23
1.15
PALMOLIVE AUTO GEL
1.15
1.08
SUNLIGHT LEMON AUTO
1.09
1.00
Weighted Average
1.41
1.32
Product Pair
Table A8.2. Dish Detergent: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
DIAL AUTO DISH DETER
1.05
1.20
PALMOLIVE AUTO GEL
1.11
1.18
SUNLIGHT LEMON AUTO
1.08
1.18
JOY LEMON
1.09
1.17
LEMON DAWN
1.05
1.15
DAWN LEMON
1.08
1.15
SUNLIGHT AUTO DISH
1.09
1.13
SUNLIGHT AUTO DISH
1.09
1.13
SUNLIGHT AUTO GEL
1.06
1.13
PALMOLIVE AUTO DISH
1.05
1.12
SUNLIGHT AUTO DISH
1.06
1.12
Weighted Average
1.07
1.14
Product Pair
Table A9.1. Frozen Entrees: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
CELENTANO CHEESE RAV
2.53
2.72
L.C. BAKED CHEESE RA
1.59
1.71
MRS BELGO'S MEAT RAV
1.52
1.77
MRS BELGO'S CHEESE R
1.50
1.70
TOASTED CHEESE RAVIO
1.45
1.42
HLTHY CHOICE MACARON
1.41
1.43
STFR LXP CHEESE RAVI
1.36
1.53
ITALIA MEAT TORTELLI
1.21
1.50
ORE-IDA CHEESE TORTE
1.19
1.31
STFRS MAC & CHEESE
1.17
1.13
ITALIA CHEESE RAVIOL
1.12
1.28
ITALIA MEAT RAVIOLI
1.12
1.29
LC SWEDISH MEATBALLS
1.09
1.06
LC CAFE CLSC GLAZED
1.06
1.05
FLORESTA MEAT TORTEL
0.85
0.93
Weighted Average
1.22
1.26
Product Pair
Table A9.2. Frozen Entrees: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
LC SWEDISH MEATBALLS
1.21
1.25
STFRS MAC & CHEESE
1.21
1.25
HLTHY CHOICE MACARON
1.27
1.25
LC CAFE CLSC GLAZED
1.15
1.16
TOASTED CHEESE RAVIO
1.14
1.16
STFR LXP CHEESE RAVI
1.19
1.05
L.C. BAKED CHEESE RA
1.13
1.05
ITALIA CHEESE RAVIOL
1.19
1.04
ORE-IDA CHEESE TORTE
1.15
1.04
ITALIA MEAT RAVIOLI
1.19
1.03
MRS BELGO'S CHEESE R
1.17
1.03
ITALIA MEAT TORTELLI
1.27
1.02
CELENTANO CHEESE RAV
1.09
1.02
MRS BELGO'S MEAT RAV
1.17
1.00
FLORESTA MEAT TORTEL
1.07
0.98
Weighted Average
1.18
1.15
Product Pair
Table A10.1. Frozen Juice: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
MM PINK LEMONADE
3.51
1.88
WELCH'S 100% WHITE G
2.23
1.61
MM FRUIT PUNCH
2.18
1.59
MM FRUIT PUNCH
1.96
1.39
SUNKIST PINK LEMONAD
1.91
3.72
HAWAIIAN PUNCH FRT J
1.87
1.41
MM LEMONADE
1.80
1.26
MM PINK LEMONADE
1.79
1.26
~SENECA APPLE JUICE
1.57
1.64
~MM ORANGE JUICE
1.52
2.02
~SENECA APPLE JUICE
1.49
1.09
MINUTE MAID GRAPEFRU
1.48
1.28
DOLE PINEAPPLE ORANG
1.46
1.32
MM ORANGE JUICE
1.43
1.32
WELCH'S CRAN/RASP JC
1.42
1.35
MM ORANGE JUICE W/CA
1.33
1.36
MM ORANGE JUICE
1.32
1.24
TREE TOP APPLE JUICE
1.31
1.28
TREE TOP APPLE JUICE
1.30
1.25
WELCH 100% GRAPE JCE
1.27
1.21
TROP ORANGE JUICE
1.27
1.20
WELCH'S WHITE GRAPE
1.26
1.09
CITRUS HILL ORANGE J
1.25
1.18
TROP SB ORANGE JUICE
1.25
1.17
CITRUS HILL ORANGE J
1.21
1.15
WELCH'S GRAPE JUICE
1.18
1.04
HAWAIIAN PUNCH FRT J
1.11
2.20
MM PINK GRAPEFRUIT J
1.11
1.19
SUNKIST ORANGE JUICE
0.98
0.88
~TROP TWISTER CRAN/R
0.78
0.89
WELCH ADE ORANGE
0.75
0.93
~MINUTE MAID CRANBER
0.72
0.81
SUNKIST PINK LEMONAD
0.48
1.28
Weighted Average
1.41
1.28
Product Pair
Table A10.2. Frozen Juice: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
SUNKIST PINK LEMONAD
1.76
2.62
MM PINK LEMONADE
1.33
2.48
MM FRUIT PUNCH
1.54
2.11
MM FRUIT PUNCH
1.44
2.04
MM PINK LEMONADE
1.43
2.03
MM LEMONADE
1.41
2.02
~SENECA APPLE JUICE
1.40
2.02
HAWAIIAN PUNCH FRT J
1.45
1.92
TREE TOP APPLE JUICE
1.81
1.85
WELCH'S WHITE GRAPE
1.53
1.76
WELCH'S 100% WHITE G
1.27
1.76
WELCH'S GRAPE JUICE
1.50
1.70
TREE TOP APPLE JUICE
1.40
1.47
DOLE PINEAPPLE ORANG
1.29
1.44
MINUTE MAID GRAPEFRU
1.24
1.42
MM PINK GRAPEFRUIT J
1.51
1.41
SUNKIST ORANGE JUICE
1.23
1.36
WELCH 100% GRAPE JCE
1.28
1.34
WELCH ADE ORANGE
1.62
1.31
~MINUTE MAID CRANBER
1.45
1.29
MM ORANGE JUICE
1.21
1.28
TROP SB ORANGE JUICE
1.20
1.28
~TROP TWISTER CRAN/R
1.47
1.28
WELCH'S CRAN/RASP JC
1.21
1.28
CITRUS HILL ORANGE J
1.17
1.27
MM ORANGE JUICE W/CA
1.30
1.27
MM ORANGE JUICE
1.17
1.26
TROP ORANGE JUICE
1.20
1.26
CITRUS HILL ORANGE J
1.20
1.23
~SENECA APPLE JUICE
1.32
1.20
~MM ORANGE JUICE
1.50
1.12
HAWAIIAN PUNCH FRT J
1.42
0.71
SUNKIST PINK LEMONAD
1.94
0.25
Weighted Average
1.31
1.46
Product Pair
Table A11.1. Fabric Softener: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
~BOUNCE SINGLE
2.40
1.54
BOUNCE SINGLE SCENTE
2.01
1.89
~DOWNY REG REFILL
1.92
1.61
~DOWNY REG REFILL
1.90
1.59
~DOWNY SUNRISE REFIL
1.90
1.60
~DOWNY SUNRISE REFIL
1.88
1.58
DOWNY ULTRA REFILL
1.68
1.49
~DOWNY ULTRA REFILL
1.68
1.49
BOUNCE
1.63
1.47
DOWNY ULTRA REFILL S
1.60
1.48
DOWNY ULTRA REFILL B
1.60
1.48
DOWNY ULTRA REFILL B
1.53
1.47
DOWNY ULTRA REFILL S
1.53
1.47
Weighted Average
1.77
1.56
Product Pair
Table A11.2. Fabric Softener: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
~BOUNCE SINGLE
1.13
1.76
~DOWNY SUNRISE REFIL
1.08
1.28
~DOWNY REG REFILL
1.07
1.28
~DOWNY SUNRISE REFIL
1.08
1.28
~DOWNY REG REFILL
1.07
1.28
DOWNY ULTRA REFILL
1.09
1.23
~DOWNY ULTRA REFILL
1.09
1.23
BOUNCE
1.04
1.16
DOWNY ULTRA REFILL S
1.05
1.14
DOWNY ULTRA REFILL B
1.05
1.14
BOUNCE SINGLE SCENTE
1.03
1.09
DOWNY ULTRA REFILL S
1.05
1.09
DOWNY ULTRA REFILL B
1.05
1.09
Weighted Average
1.06
1.21
Product Pair
Table A12.1. Grooming Products: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
~SLIM TWIN+ CART
3.58
3.01
SLIM TWIN DISP PPD $
2.86
1.79
TRAC II PLUS CART 10
2.44
2.06
~SLIM TWIN CARTRIDGE
2.05
1.71
GOOD NEWS PIVOT PLS
1.62
1.42
GOOD NEWS PIVOT PLUS
1.49
1.31
TC DISP RAZOR SINGLE
1.41
1.19
TOP CARE DOUBLE EDGE
1.33
1.02
TC DISP RAZOR TWIN P
1.21
1.12
TOP CARE DOUBLE EDGE
0.75
1.66
Weighted Average
1.92
1.57
Product Pair
Table A12.2. Grooming Products: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
TC DISP RAZOR SINGLE
1.82
2.16
SLIM TWIN DISP PPD $
1.17
1.87
TC DISP RAZOR TWIN P
1.37
1.47
TOP CARE DOUBLE EDGE
1.10
1.42
TOP CARE DOUBLE EDGE
1.13
1.28
~SLIM TWIN+ CART
1.06
1.26
GOOD NEWS PIVOT PLS
1.09
1.25
~SLIM TWIN CARTRIDGE
1.04
1.24
GOOD NEWS PIVOT PLUS
1.09
1.24
TRAC II PLUS CART 10
1.04
1.24
Weighted Average
1.12
1.37
Product Pair
Table A13.1. Laundry Detergents: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
ULTRA IVORY-SNOW
1.84
1.64
ERA H D LIQ DETERG
1.72
1.61
WOOLITE LIQUID
1.63
1.40
WOOLITE LIQUID
1.52
1.36
~ULTRA TDE W/BLCH
1.49
1.36
SOLO HD LIQ DETG
1.48
1.41
NON PHOS CONC ALL DE
1.42
1.38
TIDE W/BLEACH ULTRA
1.31
1.26
~ULTRA TIDE W/BLEACH
1.27
1.22
NP WISK HD LIQ DET
1.17
1.14
FAB ULTRA LIQUID
1.16
1.17
~ULTRA SURF LIQ
1.15
1.15
SOLO HD LIQUID DETG.
1.07
1.05
ERA H D LIQ DETERG
1.06
1.04
ULTRA BOLD
1.05
1.03
ULTRA WISK W/BLEACH
1.05
1.00
Weighted Average
1.26
1.20
Product Pair
Table A13.2. Laundry Detergents: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
WOOLITE LIQUID
1.11
1.29
WOOLITE LIQUID
1.06
1.19
ULTRA IVORY-SNOW
1.03
1.15
~ULTRA TDE W/BLCH
1.04
1.14
SOLO HD LIQ DETG
1.05
1.10
ERA H D LIQ DETERG
1.03
1.10
TIDE W/BLEACH ULTRA
1.02
1.07
ULTRA WISK W/BLEACH
1.02
1.07
FAB ULTRA LIQUID
1.06
1.06
NON PHOS CONC ALL DE
1.03
1.06
~ULTRA TIDE W/BLEACH
1.01
1.05
ULTRA BOLD
1.02
1.05
ERA H D LIQ DETERG
1.03
1.04
SOLO HD LIQUID DETG.
1.03
1.04
NP WISK HD LIQ DET
1.01
1.04
~ULTRA SURF LIQ
1.04
1.03
Weighted Average
1.03
1.07
Product Pair
Table A14.1. Oatmeal: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
QUICK QUAKER OATS
1.77
1.31
QUICK QUAKER OATS
1.51
1.20
QUAKER INST OATML RS
1.48
1.27
QUAKER INSTANT OATME
1.47
1.26
QUAKER INST OATML MP
1.40
1.18
Weighted Average
1.55
1.24
Product Pair
Table A14.2. Oatmeal: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
QUICK QUAKER OATS
1.11
1.63
QUAKER INST OATML MP
1.09
1.29
QUAKER INSTANT OATME
1.09
1.27
QUAKER INST OATML RS
1.08
1.27
QUICK QUAKER OATS
1.08
1.24
Weighted Average
1.09
1.38
Product Pair
Table A15.1. Snack Cracker: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
SUNSHINE CHEEZ IT
1.61
1.30
KEEBLER CLUB CRACKE
1.43
1.21
TOWN HOUSE CHEDDAR J
1.52
1.23
NABISCO RITZ CRACKER
1.65
1.36
NABISCO RITZ CRACKER
1.90
1.49
~NABISCO RITZ BITS
1.65
1.32
NABISCO CHEESE NIPS
1.67
1.32
WORTZ SALTINES
0.48
0.66
Weighted Average
1.49
1.24
Product Pair
Table A15.2. Snack Cracker: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
SUNSHINE CHEEZ IT
1.15
1.43
KEEBLER CLUB CRACKE
1.12
1.32
TOWN HOUSE CHEDDAR J
1.16
1.43
NABISCO RITZ CRACKER
1.09
1.32
NABISCO RITZ CRACKER
1.13
1.43
~NABISCO RITZ BITS
1.13
1.40
NABISCO CHEESE NIPS
1.16
1.48
WORTZ SALTINES
1.92
1.38
Weighted Average
1.23
1.40
Product Pair
Table A16.1. Tooth Brushes: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
PEPSODENT T/B SOFT P
2.47
1.19
PEPSODENT T/B MEDIUM
2.58
1.19
CREST T.B. #6 SOFT S
12.31
3.26
CREST T.B. #2 MED ST
12.87
3.28
CREST T.B. #5 SOFT S
13.98
3.31
CREST T.B. #1 MED ST
13.74
3.31
REACH BETWEEN SOFT
12.25
2.91
REACH BETWEEN MEDIUM
10.92
2.91
J&J FLOSS WAX REG
2.03
1.52
J&J FLOSS UNW REG
2.04
1.52
J&J FLOSS WAX MINT
2.04
1.53
Weighted Average
7.93
2.36
Product Pair
Table A16.2. Tooth Brushes: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
PEPSODENT T/B SOFT P
2.00
4.15
PEPSODENT T/B MEDIUM
1.96
4.26
CREST T.B. #6 SOFT S
1.15
4.33
CREST T.B. #2 MED ST
1.14
4.49
CREST T.B. #5 SOFT S
1.15
4.85
CREST T.B. #1 MED ST
1.14
4.75
REACH BETWEEN SOFT
1.21
5.08
REACH BETWEEN MEDIUM
1.21
4.53
J&J FLOSS WAX REG
1.42
1.90
J&J FLOSS UNW REG
1.42
1.91
J&J FLOSS WAX MINT
1.42
1.89
Weighted Average
1.38
3.83
Product Pair
Table A17.1. Canned Tuna: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
C O S LITE TUNA - WA
1.89
1.60
C O S LITE TUNA - WA
1.89
1.59
C O S LITE TUNA - WA
1.88
1.51
C O S SOLID WHITE -
1.23
1.17
C O S CHUNK LIGHT WA
1.12
1.10
C O S SOLID WHITE -
1.09
1.09
C O S CHUNK LIGHT WA
1.08
1.05
Weighted Average
1.23
1.16
Product Pair
Table A17.2. Canned Tuna: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
C O S LITE TUNA - WA
1.32
1.64
C O S LITE TUNA - WA
1.26
1.50
C O S LITE TUNA - WA
1.24
1.45
C O S SOLID WHITE -
1.16
1.21
C O S SOLID WHITE -
1.20
1.19
C O S CHUNK LIGHT WA
1.12
1.14
C O S CHUNK LIGHT WA
1.08
1.10
Weighted Average
1.14
1.20
Product Pair
Table A18.1. Tooth Paste: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
ARM & HAMMER DENTAL
1.57
1.32
PEPSODENT TP W/BAKIN
0.50
0.52
AIM TARTER GEL #
0.69
0.74
PEPSODENT W/FLORIDE
1.53
1.49
CLOSE UP BAKING SODA
1.09
0.95
CLOSE-UP TARTAR CONT
1.22
1.15
ARM & HAMMER DENTAL
1.70
1.45
~COLGATE TARTER GEL
1.70
1.56
*COLGATE TARTAR REG
1.39
1.22
*COLGATE TARTAR GEL
1.42
1.25
~COLGATE TARTER GEL
1.38
1.24
*CREST TRT GEL
1.41
1.25
*CREST REG
2.22
1.60
*CREST TRT REG
1.38
1.23
*AQUA FRESH TOOTHPAS
2.16
1.65
AQUAFRESH TOOTHPASTE
2.05
1.49
Weighted Average
1.46
1.26
Product Pair
Table A18.2. Tooth Paste: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
ARM & HAMMER DENTAL
1.09
1.29
PEPSODENT TP W/BAKIN
1.33
1.29
AIM TARTER GEL #
1.28
1.20
PEPSODENT W/FLORIDE
1.39
1.43
CLOSE UP BAKING SODA
1.12
1.29
CLOSE-UP TARTAR CONT
1.11
1.19
ARM & HAMMER DENTAL
1.10
1.29
~COLGATE TARTER GEL
1.08
1.18
*COLGATE TARTAR REG
1.06
1.20
*COLGATE TARTAR GEL
1.06
1.20
~COLGATE TARTER GEL
1.08
1.21
*CREST TRT GEL
1.06
1.20
*CREST REG
1.03
1.42
*CREST TRT REG
1.06
1.20
*AQUA FRESH TOOTHPAS
1.08
1.42
AQUAFRESH TOOTHPASTE
1.03
1.41
Weighted Average
1.12
1.28
Product Pair
Table A19.1. Soft Drinks: National Brand Markup
NB Markup
Based on WP
NB Markup
Based on RP
PEPSI COLA N/R
1.81
1.57
PEPSI DIET N/R
1.91
1.61
PEPSI COLA
2.10
1.57
SCHWEPPS TONIC N/R
1.82
1.29
SCHWEPPS GINGER ALE
1.56
1.24
SCHWEPPES DIET TONIC
1.79
1.28
SCHWEPPES LIME SELTZ
1.95
1.25
SCHWEPPES GINGER ALE
1.83
1.41
CANADA DRY GINGER AL
1.90
1.43
CANADA DRY TONIC WAT
1.98
1.43
R.C. COLA
1.59
1.32
ROYAL CROWN COLA
1.70
1.35
HIRES ROOT BEER N/R
1.98
1.90
SUNKIST ORANGE
2.23
1.59
COCA-COLA CLASSIC
1.83
1.57
DIET COKE
1.91
1.62
MIN MAID FRUIT PUNCH
2.19
1.80
BARQ'S ROOT BEER
2.79
1.87
BARQ'S DIET RT BEER
2.12
1.65
NEW YORK SELTZER COL
1.80
1.50
A W RT BEER REG
1.55
1.31
A W ROOT BEER SF
1.51
1.30
SEAGRAMS GINGERALE 1
2.42
1.38
SEAGRAMS TONIC 1 LIT
2.48
1.46
SEAGRAMS GINGR ALE$
1.94
1.68
SEAGRAM'S LEMON LIME
1.75
1.51
CANFIELDS LEMON SELT
1.98
1.30
CANFIELD GINGER ALE
2.37
1.79
CANFIELD TONIC
2.62
1.93
CANFIELD COLA NR
1.66
1.66
CANFIELD DIET COLA N
2.09
1.64
CANFIELD SWISS CREME
1.75
1.52
CANFIELD COLA 3LITER
2.02
1.30
Weighted Average
1.68
1.45
Product Pair
Table A19.2. Soft Drinks: Retailer’s Markup
Retailer’s
Markup on NB
Retailer’s
Markup on PL
PEPSI COLA N/R
1.12
1.29
PEPSI DIET N/R
1.10
1.31
PEPSI COLA
1.05
1.40
SCHWEPPS TONIC N/R
1.24
1.74
SCHWEPPS GINGER ALE
1.33
1.67
SCHWEPPES DIET TONIC
1.24
1.74
SCHWEPPES LIME SELTZ
1.12
1.75
SCHWEPPES GINGER ALE
1.05
1.36
CANADA DRY GINGER AL
1.28
1.70
CANADA DRY TONIC WAT
1.28
1.77
R.C. COLA
1.08
1.30
ROYAL CROWN COLA
1.12
1.40
HIRES ROOT BEER N/R
1.24
1.29
SUNKIST ORANGE
0.96
1.34
COCA-COLA CLASSIC
1.11
1.29
DIET COKE
1.11
1.31
MIN MAID FRUIT PUNCH
1.17
1.42
BARQ'S ROOT BEER
0.96
1.43
BARQ'S DIET RT BEER
1.05
1.35
NEW YORK SELTZER COL
1.35
1.63
A W RT BEER REG
1.09
1.30
A W ROOT BEER SF
1.14
1.32
SEAGRAMS GINGERALE 1
1.18
2.07
SEAGRAMS TONIC 1 LIT
1.25
2.12
SEAGRAMS GINGR ALE$
1.23
1.42
SEAGRAM'S LEMON LIME
1.27
1.47
CANFIELDS LEMON SELT
1.16
1.76
CANFIELD GINGER ALE
1.17
1.55
CANFIELD TONIC
1.17
1.59
CANFIELD COLA NR
1.25
1.25
CANFIELD DIET COLA N
0.97
1.23
CANFIELD SWISS CREME
1.21
1.40
CANFIELD COLA 3LITER
0.98
1.52
Weighted Average
1.29
1.48
Product Pair
Chart 1. Average National Brand Markups Based on the Wholesale and Retail Prices
Forzen Entrees
Canned Tuna
Laundry Detergents
Cheeses
Bottled Juices
Frozen Juices
Dish Detergents
Toothpastes
Snack Crackers
Cereals
Canned Soups
Oatmeals
Cookies
Soft Drinks
Fabric Softeners
Grooming Products
Analgesics
Crackers
Tooth Brushes
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
Wholesale Prices
Retail Prices
Chart 2. National Brand Markup Based on Wholesale Prices and the Retailer Markups
Forzen Entrees
Canned Tuna
Laundry Detergents
Cheeses
Bottled Juices
Frozen Juices
Dish Detergents
Toothpastes
Snack Crackers
Cereals
Canned Soups
Oatmeals
Cookies
Soft Drinks
Fabric Softeners
Grooming Products
Analgesics
Crackers
Tooth Brushes
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
Retailer Markup on National Brand
Retailer Markup on Private Label
National Brand Markup
Chart 3. Retailer's Markup on National Brand and Private Label Products
Forzen Entrees
Canned Tuna
Laundry Detergents
Cheeses
Bottled Juices
Frozen Juices
Dish Detergents
Toothpastes
Snack Crackers
Cereals
Canned Soups
Oatmeals
Cookies
Soft Drinks
Fabric Softeners
Grooming Products
Analgesics
Crackers
Tooth Brushes
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
Retailer Markup on National Brand
Retailer Markup on Private Label
4.00